A best-case Rosenthal equilibrium based coordination mechanism for N-person online routing games of connected and automated vehicles
Center for Cyber-Physical Systems; Department of Civil, Environmental, and Geospatial Engineering
In this paper, the authors propose a best-case Rosenthal equilibrium based coordination mechanism for online automated routing decisions of connected and automated vehicles (CAVs) in a connected transportation network system. The objective of the coorination mechanism is to coordinate between the multiple equilibria in an n-person online routing game so that the authors can make better route choice decisions for CAVs. The mechanism is modeled as a pure-strategy congestion game. The model assumes that individual CAVs are non-cooperative and try to minimize their own travel time in the network. The proposed mechanism tries to coordinate between these equilibria considering both total travel time and individual payoff. Based on the original Rosenthal’s integer programming formulation of a congestion game, the authors propose an integer linear programming formulation that can be directly solved by a solver in a column generation based solution framework. Numerical experiments using Sioux Falls network substantiate the existence of multiple equilibria and validate that the solution derived from the proposed algorithm is a Nash equilibrium. The convergence of the algorithm is also consolidated from the experiment results.
Transportation Research Board 98th Annual Meeting
A best-case Rosenthal equilibrium based coordination mechanism for N-person online routing games of connected and automated vehicles.
Transportation Research Board 98th Annual Meeting.
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/683